fix(conv1d): prevent gradient error by removing in-place ops #82
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🛠️ Fix: Avoid in-place modification in conv1d_step to preserve autograd graph
This PR addresses a critical issue in the conv1d_step function where the in-place update of conv_state (.copy_() and [..., -1:, :] = x) was interfering with PyTorch's autograd system, breaking gradient computation during backpropagation. This change ensures that conv_state is safely updated by creating a new tensor, preserving the computational graph and enabling correct gradient flow through time.